Natural Language Processing (NLP) is a hotbed of research in data science these days and one of the most common applications of NLP is sentiment analysis. From opinion polls to creating entire marketing strategies, this domain has completely reshaped the way businesses work, which is why this is an area every data scientist must be familiar with.

Thousands of text documents can be processed for sentiment (and other features including named entities, topics, themes, etc.) in seconds, compared to the hours it would take a team of people to manually complete the same task.

In this article, we will learn how to solve the Twitter Sentiment Analysis Practice Problem.

CloudQuant Thoughts… Of course we already have cleaned Twitter (SMA) and Stocktwits sentiment data available to our users. You can experiment with it today at app.CloudQuant.com, utilizing the data to add to or make US Equity trading decisions using our free backtesting system.

On the eve of a 6-month pilot, Drive.ai details its self-driving car plans

It’s been almost a year since Waymo, the autonomous vehicle division of Google parent Alphabet, became the first company to operate autonomous cars on public roads without drivers behind the wheel. Now Drive.ai intends to follow suit.

This month, the Silicon Valley startup will set loose a fleet of self-driving Nissan NV200 vans in Frisco, Texas. They won’t be completely autonomous — a small army of safety drivers and remote operators will ensure rides go off without a hitch. And the vehicles will be contained in a geofenced area.
2018-07-30 00:00:00 Read the full story.CloudQuant Thoughts… Whilst it’s geofenced area is quite small, this is still a major step forward. I particularly enjoyed the cyclist trying to indicate to the driver that he couldn’t see very well because of the sun only to realize that there was no driver.

Amazon challenges ACLU study on facial recognition tech and police

Amazon’s Matt Wood, a leader on the Amazon Web Services machine learning team, expressed skepticism about an experiment the ACLU conducted using Rekognition to compare headshots of the members of Congress with a database of 25,000 mugshots. The test set Rekognition to make matches with an 80 percent confidence rating, according to Amazon. The ACLU says Rekognition incorrectly matched 28 members of Congress to people pictured in arrest photos. “The false matches were disproportionately of people of color, including six members of the Congressional Black Caucus,” the ACLU said in a blog post.

In Wood’s response, he says Amazon recreated the ACLU experiment comparing photos from members of Congress to a database of 850,000 faces with a 99 percent confidence threshold. Amazon says it saw a 0 percent misidentification rate, “despite the fact that we are comparing against a larger corpus of faces.”. Wood also wrote “The default confidence threshold for Rekognition is 80%, which is good for a broad set of general use cases (such as identifying objects, or celebrities on social media), but it’s not the right one for public safety use cases”.

Everyday Lessons from the Facebook Data Scandal

As the facts come out slowly, there are some realities about what Facebook did and did not do that are highly misguided. There are other realities of the nature of big data capture and digital surveillance in our lives that we must reconsider. Indeed, the notion of privacy and protection are being redefined practically, even if we as a society are not ready for it. Let’s take a closer look at some of the lessons:

CloudQuant Thoughts… A very well written piece hitting all the points on how we should all be carefully policing our own personal data.

UPS Is Thinking About a Future With Autonomous Vehicles

UPS (UPS) is caught in the middle on whether to aggressively pursue autonomous vehicles. “In autonomous, we are kind of in between,” UPS CFO Richard Peretz tells TheStreet. Peretz says UPS’ autonomous driving efforts are being done in test environments, not on public roads. “The driver is an important part of the value proposition for our customers,” Peretz says.

In a blog post on its website, UPS acknowledges the inevitable army of self-driving vehicles likely to disrupt many industries.

Below the Fold…

Over 200 of the Best Machine Learning, NLP, and Python Tutorials — 2018 Edition

The article contains the best tutorial content that I’ve found so far. It’s by no means an exhaustive list of every ML-related tutorial on the web — that would be overwhelming and duplicative. Plus, there is a bunch of mediocre content out there. My goal was to link to the best tutorials I found on the important subtopics within machine learning and NLP.

By tutorial, I’m referring to introductory content that is intending to teach a concept succinctly. I’ve avoided including chapters of books, which have a greater breadth of coverage, and research papers, which generally don’t do a good job in teaching concepts. Why not just buy a book? Tutorials are helpful when you’re trying to learn a specific niche topic or want to get different perspectives.

Faster Machine Learning – The Big Deal With GPUs

If you’ve been following data science and machine learning, you’ve probably heard the term GPU. But what exactly is a GPU? And why are they so popular all of a sudden?

A Graphics Processing Unit (GPU) is a computer chip that can perform massively parallel computations exceedingly fast. Throughout the 2000s, companies like NVIDIA and AMD invested in GPUs to improve performance for video gaming and 3D modeling. As developers designed increasingly realistic looking games, they needed more powerful hardware to render the game images. Researchers have long experimented with using GPUs for more than just games, but the last 10 years have seen an expansion of GPUs into many data science applications, including deep learning.
2018-07-27 12:13:19-05:00 Read the full story.

The 3 next steps in conversational AI

Conversational AI is a subfield of artificial intelligence focused on producing natural and seamless conversations between humans and computers. We’ve seen several amazing advances on this front in recent years, with significant improvements in automatic speech recognition (ASR), text to speech (TTS), and intent recognition, as well as the rocketship growth of voice assistant devices like the Amazon Echo and Google Home, with estimates of close to 100 million devices in homes in 2018.

But we’re still a long way away from the fluent human-machine conversation promised in science fiction. Here are some key advances we should see over the next decade that could get us closer to that long-term vision.
2018-07-29 00:00:00 Read the full story.

Top Conferences In Singapore For Data Scientists To Attend

Singapore has grown to have a prominent position in Analytics adoption, especially if we compare its regional peers. It also wins on being a financial and technology hub in south-east Asia. Data science adoption is increasing significantly in the organizations in Singapore.

Here we present top conferences on Analytics and Data science that have created a niche over time.

Predictive analytics is key to insurance sector competitiveness

Access to data is essential to the success of insurance companies—data and analytics play a critical role in sales and distribution, fraud detection and prevention, and underwriting and claims management. They also provide insurance companies with valuable customer insights.

One particular group of techniques—predictive analytics, which uses data and statistical algorithms to analyse historical data to forecast behaviour—continues to disrupt the insurance sector.

Financial regulators embrace AI and machine learning

With increasing institutional use of Al and machine learning methods, more and more industry regulators are making use of such software to provide financial stability through services and systemic risk surveillance.

Central to the UK Financial Conduct Authority’s (FCA) agenda is their intent to develop “both their technology side – cloud analytics – as well as building out our human side – our data science capability” to allow an “osmotic” expansion across the wider organisation, “effectively enabling us to leverage machine learning,” says head of regtech and advanced analytics at FCA, Nick Cook.

Here are four key regulatory areas set for disruption by AI and machine learning:

AI Weekly: For self-driving cars, the path to public acceptance is transparency and an abundance of caution

Self-driving cars have transformative potential. They’re poised to reduce traffic fatalities, ease congestion, and even decrease carbon emissions — not to mention cutting down on the amount of city space dedicated to parking. There’s just one problem: Most people are afraid of them.

Two studies this week — one by the Brookings Institution and another from the Advocates for Highway and Auto Safety (AHAS) — found that a majority of Americans aren’t convinced of driverless cars’ safety. More than 60 percent of respondents to the Brookings poll said that they were “not inclined” to ride in self-driving cars, and almost 70 percent of those surveyed by the AHAS expressed “concerns” about sharing the road with them.

The sentiments echo those expressed in a poll conducted earlier this year by think tank HNTB, which found that 59 percent of people expect self-driving cars to be “no safer” than cars controlled by human drivers. That’s despite the fact that more than 94 percent of car crashes are caused by human error and that in 2016 the top three causes of traffic fatalities were distracted driving, drunk driving, and speeding.

Kixeye enlists players to provide customer support for Battle Pirates

Kixeye launched its Battle Pirates strategy game on Facebook seven years ago, but the game still has a loyal following of 100,000 players. The audience isn’t big enough to serve with Kixeye’s own internal technical support team, but the San Francisco company came up with a novel resource to get the job done: the players themselves.

The team created a machine learning and natural language processing system to route support questions to the people who are most likely to be able to answer it. The players are rated on quality of their answers, and the ones who have high ratings will get more questions sent their way. And Getze said the players are compensated in the form of their favorite currency, the virtual currency in the game.

Normally, the players have to earn that currency or pay real money for it. But as participants in the Peer2Peer program, they can earn the equivalent of $2 per ticket answered. About 2 percent to 3 percent of the players participate, and that’s all Kixeye needs right now. The players have to pass a test demonstrating their knowledge of the game.
2018-07-27 00:00:00 Read the full story.

Twitter uses AI to promote more “healthy conversation”

Twitter saw a slight dip in monthly active users during the second quarter of 2018, but exceeded revenue expectations.

In June, the company said it was now proactively identifying and “challenging” 9.9 million spam accounts per week. The move is part of Twitter’s ongoing efforts to promote more “healthy conversation” on the platform. Twitter CEO Jack Dorsey said during the earnings call. “We made a major shift this year in shifting more of our model and enforcement towards behavior and conduct on the platform, rather than content. That’s entirely machine learning and deep learning-driven.”
2018-07-27 00:00:00 Read the full story.

EagleView Technologies, a privately held aerial imagery and data analytics company headquartered in Bothell, Wash., says it intends to acquire Spookfish, an Australian company that’s in the same business. The deal opens the way for EagleView to deploy Spookfish’s advanced aerial camera technology in North America, and establishes a presence for EagleView in the Australian market.

Thanks to the tech upgrade, EagleView will be able to deliver aerial imagery at significantly higher resolution than before, augmented by machine learning processes. The company’s customers include insurance underwriters, tax assessors, city planners, contractors, utilities and others who need accurate information about property conditions or changes.

“Elon has made some interesting statements of late, so I would take his pronouncements with a grain of salt,” Chishti, who is chairman and CEO of surging AI firm Afiniti, tells TheStreet. “AI is just a way to identify patterns in complex fields, it’s not going to nuke the world — there is no chance of that. I think the visions of the impending apocalypse as a result of robot intelligence is fanciful — so I wouldn’t be overly concerned about Elon Musk’s perspective on it.”
2018-07-30 07:00:00-04:00 Read the full story.

AI Assistant-Equipped Smartphones Will Comprise Half Of New Releases This Year

Artificial intelligence is becoming a major aspect of new smartphones. An industry source says around half of the devices that are launching this year will come equipped with an AI assistant, hinting at the stronger demand for more advanced phone features.

Industry consulting firm Strategy Analytics Inc. said via Korea Herald Sunday that about 47.7 percent of smartphones that will be sold on the global market will have some sort of on-device AI assistant. To show just how demand for AI assistant increased, the predicted figure is up from the 36.6 percent last year.
2018-07-29 22:55:57-04:00 Read the full story.

The system is being used in 230 hospitals around the world to help doctors diagnose patients. It does so by using artificial intelligence to analyse their medical data in combination with information from hundreds of medical journals. Since 2015, Watson has given advice on nearly 60,000 patients.

A report from health website Stat News states that internal documents shared by IBM Watson’s former deputy health chief Andrew Norden provided strong criticism of the Watson for Oncology system. It stated that the “often inaccurate” suggestions made by the product raise “serious questions about the process for building content and the underlying technology”.

For example, Watson reportedly suggested giving the drug Bevacizumab to a 65-year-old man diagnosed with lung cancer, who also seemed to have severe bleeding. One of the side effects of the drug is that can lead to “severe or fatal hemorrhage”.

According to the documents reviewed by Stat, a doctor at Florida’s Jupiter Hospital told IBM: “We bought it for marketing and with hopes that you would achieve the vision. We can’t use it for most cases.”

PAYWALLED ARTICLES

Facebook’s stock dropped by $120 billion this week, but critics are dead wrong for calling it ‘doomed’

Even though Facebook saw its market valuation fall by 20% Thursday, CEO Mark Zuckerberg and company still have plenty to smile about. AP

You might have thought from the tone of the coverage following Facebook’s earnings report Wednesday that the company was on the brink of bankruptcy.

The results were repeatedly dubbed “disastrous” by reporters and analysts alike. The company was called ” friendless ” in headlines. And following the report , in…
2018-07-27 00:00:00 Read the full story.

Inventor of Viagra raises funding to treat 7,000 rare diseases

the world’s rarest diseases

Dr David Brown, the scientist who developed the blockbuster treatment for erectile dysfunction for Pfizer, is the co-founder of Healx, a UK medical tech startup that uses machine learning to find treatments for 7,000 rare conditions that do not currently have an approved method of treatment.

The $10m (£7.6m) initial funding round, led by European venture capital investor Balderton Capital, will allow Healx to develop new technology for what it described as “automated large-scale drug discovery”…….
2018-07-26 00:00:00 Read the full story.

The top tech executive at $41 billion investment firm Fortress is leaving to start his own data-focused fund

Steve Helber/AP

Hylton Socher, the chief technology and information officer of Fortress Investment Group, the $41 billion hedge fund, is leaving the fund to start his own venture, Business Insider has learned.

Socher, whose career at Fortress spans a decade, fell down the rabbit hole of big data and other new-wave technologies sweeping Wall Street, he said in an interview.

LinkedIn Socher’s firm, which he expects to be up-and-running by the fi…
2018-07-28 00:00:00 Read the full story.

The ex-army man taking on the big data dark arts

coffee.

For the former army officer and special operations expert, it’s been an unlikely journey. He spent years fighting in Iraq and Afghanistan before launching what could be the UK’s next bet in big data and artificial intelligence.

Unsurprisingly, Bassett Cross does not come across as your typical tech chief executive. The Silicon Valley uniform of sandals and T-shirts won’t do for the ex-military man, who later worked as an investment banker at JP Morgan. He cuts a disciplined, hard-nosed figure.

His new venture – Adarga – uses AI to change the way intelligence agencies and defence companies….
2018-07-29 00:00:00 Read the full story.

Trade war and iPhone sales: What to watch for in Apple earnings

Apple CEO Tim Cook Drew Angerer/Getty Images

Apple has a chance to give investors another reason to keep Apple’s bullish streak going when it reports earnings after markets close on Tuesday . Apple shares are up 15% in the past three months, buoyed by a massive capital return program announced in April.

In its fiscal 3rd quarter earnings, which cover the three months ending in June, Apple will reveal whether the iPhones it launched last Septemb…
2018-07-29 00:00:00 Read the full story.

Amazon AI expert says government should regulate facial recognition

One of Amazon’s leading artificial intelligence experts has suggested that government intervention is needed as a watchdog to monitor the development of facial recognition for the police.

The call comes after Amazon’s own facial recognition technology, known as “Rekognition”, was slammed by an American civil rights group for its apparent inaccuracy.

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